fix: honor effective time window boundaries in cycle scheduling

tests/test_timewindow_boundaries.py

@@ -0,0 +1,154 @@
+"""Regression tests for explicit window ends and cycle scheduling."""
+
+import json
+
+import numpy as np
+import pendulum
+import pytest
+
+from akkudoktoreos.config.configabc import (
+    CycleTimeWindowSequence,
+    TimeWindow,
+    ValueTimeWindow,
+)
+from akkudoktoreos.devices.genetic.homeappliance import (
+    HomeAppliance,
+    HomeApplianceParameters,
+)
+
+
+@pytest.mark.parametrize("model", [TimeWindow, ValueTimeWindow])
+def test_end_only_window_json_round_trip(model):
+    window = model.model_validate({"start_time": "08:00", "end_time": "12:00"})
+
+    serialized = window.model_dump_json()
+
+    assert json.loads(serialized)["duration"] == "PT0S"
+    restored = model.model_validate_json(serialized)
+    assert restored.model_dump() == window.model_dump()
+    assert restored.contains(pendulum.datetime(2026, 10, 26, 9))
+
+
+@pytest.mark.parametrize(
+    ("start_date", "start_time", "end_time", "expected_end"),
+    [
+        # The missing 02:30 on the opening date must not shift Monday's end.
+        ("2026-03-29", "22:00", "02:30", "2026-03-30T02:30:00+02:00"),
+        # The explicit end lies after the spring transition.
+        ("2026-03-28", "22:00", "06:00", "2026-03-29T06:00:00+02:00"),
+        # The explicit end lies after the autumn transition.
+        ("2026-10-24", "22:00", "06:00", "2026-10-25T06:00:00+01:00"),
+    ],
+)
+def test_overnight_end_uses_clock_time_on_end_date(start_date, start_time, end_time, expected_end):
+    window = TimeWindow.model_validate({"start_time": start_time, "end_time": end_time})
+    reference = pendulum.from_format(start_date, "YYYY-MM-DD", tz="Europe/Berlin")
+
+    _, end = window._window_start_end(reference)
+
+    assert end.isoformat() == expected_end
+    assert not window.contains(end)
+    assert window.contains(end.subtract(minutes=1))
+
+
+@pytest.mark.parametrize(
+    ("config", "start", "hours", "active_steps"),
+    [
+        ({"start_time": "08:00", "end_time": "12:00"}, "2026-10-26", 24, [8, 9, 10, 11]),
+        # Duration may extend the explicit end.
+        (
+            {"start_time": "08:00", "end_time": "10:00", "duration": "4 hours"},
+            "2026-10-26",
+            24,
+            [8, 9, 10, 11],
+        ),
+        ({"start_time": "08:00", "end_time": "12:00", "month": 11}, "2026-10-26", 24, []),
+        ({"start_time": "08:00", "end_time": "12:00", "day_of_week": 1}, "2026-10-26", 24, []),
+        ({"start_time": "08:00", "end_time": "12:00", "date": "2026-10-27"}, "2026-10-26", 24, []),
+        # Include the tail of Friday's window on Saturday.
+        (
+            {"start_time": "22:00", "end_time": "06:00", "day_of_week": 4},
+            "2026-10-24",
+            24,
+            list(range(6)),
+        ),
+        # Month restrictions belong to the opening date.
+        (
+            {"start_time": "22:00", "end_time": "06:00", "month": 10},
+            "2026-11-01",
+            24,
+            list(range(6)),
+        ),
+        # Long durations can begin more than one calendar day earlier.
+        (
+            {"start_time": "08:00", "duration": "3 days", "date": "2026-10-24"},
+            "2026-10-26",
+            24,
+            list(range(24)),
+        ),
+        # Recurring windows must also appear on later horizon days.
+        ({"start_time": "08:00", "end_time": "10:00"}, "2026-10-26", 48, [8, 9, 32, 33]),
+    ],
+)
+def test_cycle_arrays_use_effective_windows(config, start, hours, active_steps):
+    window = ValueTimeWindow.model_validate({**config, "value": 0})
+    sequence = CycleTimeWindowSequence(windows=[window])
+    reference = pendulum.from_format(start, "YYYY-MM-DD", tz="UTC")
+    end = reference.add(hours=hours)
+    interval = pendulum.duration(hours=1)
+    expected = np.zeros(hours)
+    expected[active_steps] = 1
+
+    actual = sequence.cycle_to_array(0, reference, end, interval)
+    indices, matrix = sequence.cycles_to_matrix(reference, end, interval)
+
+    assert indices == [0]
+    np.testing.assert_array_equal(actual, expected)
+    np.testing.assert_array_equal(matrix[0], expected)
+
+
+@pytest.mark.parametrize(("date", "hours"), [("2026-03-29", 23), ("2026-10-25", 25)])
+def test_cycle_arrays_across_dst(date, hours):
+    window = ValueTimeWindow.model_validate(
+        {"start_time": "00:00", "end_time": "06:00", "value": 0}
+    )
+    sequence = CycleTimeWindowSequence(windows=[window])
+    start = pendulum.from_format(date, "YYYY-MM-DD", tz="Europe/Berlin")
+    end = start.add(days=1)
+    expected = np.zeros(hours)
+    expected[: hours - 18] = 1  # Five elapsed hours in spring; seven in autumn.
+
+    actual = sequence.cycle_to_array(0, start, end, pendulum.duration(hours=1))
+    _, matrix = sequence.cycles_to_matrix(start, end, pendulum.duration(hours=1))
+
+    np.testing.assert_array_equal(actual, expected)
+    np.testing.assert_array_equal(matrix[0], expected)
+
+
+def test_end_only_cycle_window_allows_appliance_starts():
+    sequence = CycleTimeWindowSequence.model_validate(
+        {"windows": [{"start_time": "08:00", "end_time": "12:00", "value": 0}]}
+    )
+    # Exercise the serialized settings used by the dashboard/API as well.
+    sequence = CycleTimeWindowSequence.model_validate_json(sequence.model_dump_json())
+    appliance = HomeAppliance(
+        parameters=HomeApplianceParameters(
+            device_id="dishwasher",
+            duration_h=2,
+            consumption_wh=2000,
+            num_cycles=1,
+            time_windows=sequence,
+        ),
+        prediction_hours=24,
+        optimization_hours=24,
+    )
+    start = pendulum.datetime(2026, 10, 26)
+    appliance.start_allowed = []
+    appliance.start_earliest = []
+    appliance.start_latest = []
+
+    appliance._build_cycle_start_allowed(
+        sequence, start, start.add(days=1), pendulum.duration(hours=1)
+    )
+
+    np.testing.assert_array_equal(np.flatnonzero(appliance.start_allowed[0]), [8, 9, 10])